Installing the Scipy Stack¶
Scientific Python distributions¶
For most users, especially on Windows and Mac, the easiest way to install the packages of the Scipy stack is to download one of these Python distributions, which includes all the key packages:
- Anaconda: A free distribution for the Scipy stack. Supports Linux, Windows and Mac.
- Enthought Canopy: The free and commercial versions include the core Scipy stack packages. Supports Linux, Windows and Mac.
- Python(x,y): A free distribution including the Scipy stack, based around the Spyder IDE. Windows only.
- WinPython: A free distribution including the Scipy stack. Windows only.
- Pyzo: A free distribution based on Python 3 (see Note on Python 3) with the IEP editor. Supports Linux and Windows.
Users on Linux can quickly install the necessary packages from repositories.
Ubuntu & Debian¶
sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose
The versions in Ubuntu 12.10 and Debian 7.0 meet the current Scipy stack specification. Users might also want to add the NeuroDebian repository for extra Scipy packages.
sudo yum install numpy scipy python-matplotlib ipython python-pandas sympy python-nose
Users of Fedora 17 and earlier should then upgrade IPython using pip:
sudo pip install --upgrade ipython
sudo emerge -aN '>=dev-python/numpy-1.6' '>=sci-libs/scipy-0.10' '>=dev-python/matplotlib-1.1' '>=dev-python/ipython-0.13' '>=dev-python/pandas-0.8' '>=dev-python/sympy-0.7' '>=dev-python/nose-1.1'
You may get some messages saying that keyword changes or USE changes are necessary in order to proceed, and that you should use --autounmask-write to write changes to config files. This is especially likely to happen if you are running Gentoo Stable rather than Gentoo Testing, as of this writing (February 2013).
If this happens, just run the above command with --autounmask-write appended, then run sudo dispatch-conf (or an alternative) to save the configuration changes, and finally run the original command again.
Macs (unlike Linux) don’t come with a package manager, but there are a couple of popular package managers you can install.
You can assemble the Scipy stack from individual packages. For details of what you need, see the specification. Packages are typically on the Python Package Index, and projects’ sites may also offer official binary packages (e.g. numpy, scipy library).
Christoph Gohlke provides pre-built Windows installers for many Python packages, including all of the core Scipy stack.
You can also build any of the Scipy packages from source, for instance if you want to get involved with development. This is easy for packages written entirely in Python, while others like numpy require compiling C code. Refer to individual projects for more details.
Note on Python 3¶
The Python language is moving from the 2.x series to Python 3. As of late 2012, all of the core Scipy Stack packages support Python 3, but some more specialist packages still only work on Python 2. The methods above will mostly install Python 2, with the exception of Pyzo.
If you choose to use the new version of the language, it should be easy to find Python 3 versions of packages in your package manager.